Gen-AI Service Guidance for Elevator Fault Resolution
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Solution Overview
Problem
Mechanics face challenges in troubleshooting and resolving faults in systems for moving people, such as elevators and escalators, due to the lack of comprehensive guidance in diagnostic software applications, which often require extensive knowledge of the systems and provide insufficient information on how to address faults.
Innovation Solution
A system utilizing a generative artificial intelligence (Gen-AI) model that identifies components and faults from diagnostic messages, generating service solution data including textual and graphical instructions, such as 3-D animations, to guide mechanics in addressing issues, trained with technical documentation, service history, and feedback data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If diagnostic software applications provide only short fault descriptions, then the application remains simple and easy to use, but the information provided is insufficient for mechanics to resolve faults without extensive system knowledge
Solution Approach 1:
The patent introduces an intermediary system comprising a server and Gen-AI model that acts as a mediator between the diagnostic software and the mechanic. When a fault is detected, the system automatically generates comprehensive service solution data including step-by-step instructions, 3-D animations, and graphical guidance, delivering detailed information without requiring the software interface itself to be complex. This intermediary layer handles the complexity of information generation while keeping the user interface simple.
2Ease of operation
If comprehensive service solution data with step-by-step instructions and 3-D animations is provided, then mechanics with limited knowledge can efficiently resolve faults, but the system complexity and resource requirements increase
Solution Approach 1:
The system implements self-service by automatically generating comprehensive service solution data without requiring human experts to manually create instructions for each fault. The Gen-AI model autonomously analyzes fault information, retrieves relevant data from databases, and produces detailed guidance including 3-D animations. This automation reduces the need for manual content creation while providing extensive guidance to mechanics.
Solution Approach 2:
The patent adds another dimension to traditional diagnostic software by incorporating 3-D animations and graphical instructions alongside textual step-by-step guidance. This multi-dimensional approach enhances ease of operation by providing visual and spatial understanding that complements traditional text-based instructions, making complex repair procedures more intuitive and easier to follow.
3Productivity
If traditional diagnostic software is used without Gen-AI, then the system operates with current technology infrastructure, but mechanics require extensive knowledge and more time to resolve faults
Solution Approach 1:
The system performs preliminary action by pre-generating comprehensive service solution data before the mechanic begins the repair process. The Gen-AI model automatically creates detailed instructions, retrieves relevant technical information, and prepares 3-D animations in advance, so that when a fault occurs, the mechanic receives ready-to-use guidance immediately, eliminating the need to search through manuals or gain extensive experience.
Data Source
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AI summary
Disclosed is a system for moving people, including: a component; and a processor configured to: receive a diagnostic message from a mobile device identifying a fault with the component; and execute a generative artificial intelligence (Gen-AI) model that identifies the component, the fault and generates service solution data for performing a service solution for addressing the fault for the component; and transmit the service solution data to the mobile device.